BERT is not The Count: Learning to Match Mathematical Statements with Proofs - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

BERT is not The Count: Learning to Match Mathematical Statements with Proofs

Résumé

We introduce a task consisting in matching a proof to a given mathematical statement. The task fits well within current research on Mathematical Information Retrieval and, more generally, mathematical article analysis (Mathematical Sciences, 2014). We present a dataset for the task (the MATCH dataset) consisting of over 180k statement-proof pairs extracted from modern mathematical research articles. We find this dataset highly representative of our task, as it consists of relatively new findings useful to mathematicians. We propose a bilinear similarity model and two decoding methods to match statements to proofs effectively. While the first decoding method matches a proof to a statement without being aware of other statements or proofs, the second method treats the task as a global matching problem. Through a symbol replacement procedure, we analyze the "insights" that pre-trained language models have in such mathematical article analysis and show that while these models perform well on this task with the best performing mean reciprocal rank of 73.7, they follow a relatively shallow symbolic analysis and matching to achieve that performance.
Fichier principal
Vignette du fichier
2023.eacl-main.260.pdf (535.15 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04129864 , version 1 (15-06-2023)

Identifiants

Citer

Weixian Waylon Li, Yftah Ziser, Maximin Coavoux, Shay B. Cohen. BERT is not The Count: Learning to Match Mathematical Statements with Proofs. European Chapter of the Association for Computational Linguistics, May 2023, Dubrovnik, Croatia. pp.3581-3593, ⟨10.18653/v1/2023.eacl-main.260⟩. ⟨hal-04129864⟩
21 Consultations
20 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More